Nattapat Boonprakong (Nat)
Hi and good day! I am a final-year PhD candidate in Human-Computer Interaction at the University of Melbourne, Australia. My research interests lie within an intersection of different disciplines such as Human-Centred Computing, Behavioural Science, Cognitive Psychology, and Physiological Sensing. My PhD research is specifically interested in Quantifying, Understanding, and Mitigating Cognitive Biases in Human-Computer Interaction (HCI).
I define myself as a computer scientist. My passion is to design and develop technologies that take into account human cognitive states, adapt with complex and constrainted mental models, and help people make decisions in real-world.
I am actively involved in research communities of cognitive bias and physiological computing. I led the organisation of two successful workshops at premier HCI venues: (1) Understanding and Mitigating Cognitive Biases in Human-AI Collaoration (CSCW ‘23) and (2) Advancing Physiological Methods in Human-Information Interaction (UbiComp/ISWC ‘24).
I am currently looking for job/postdoc opportunities. My official CV is available here.
Keywords: Cognitive Biases; Mental Models in Human-Computer Interaction; Physiological Computing; Human-Information Interaction
Outline of My Research
Human mental models are heavily influenced by Cognitive biases – systematic patterns of deviation from the norm of rational decision-making, resulting from the unconscious use of mental shortcuts to effectively sift through day-to-day decision-making. When interacting with computing systems and user interfaces, human users face a sheer amount of information and pressure to make quick decisions. Many real-world HCI scenarios suggest that computing systems can trigger and capitalise on cognitive biases; for example, the spread of misinformation, overreliance on AI explanation, dark patterns, or social engineering.
In the work with my PhD supervisors Tilman Dingler, Benjamin Tag, and Jorge Goncalves, I explore the notion of cognitive biases in HCI – how they can be reliably quantified, how they manifest in the interaction with computers, and how their undesired effects can be effectively mitigated.
A brief summary of my PhD work:
I apply physiological methods – Near Infrared Technology (fNIRs), Electrodomal Activity (EDA), and Eye-Tracking – to measure the effects of cognitive biases when reading ideologically polarised short-information (e.g., opinion tweets about climate change, abortion rights, or feminism). To overcome the unconscious nature of cognitive biases, I conduct a study to explore feasible measures of cognitive biases when people face different opinions. This work paves the first step towards the in-situ detection of cognitive biases. [CHI ‘23 Honourable Mention Paper, video]
I study individual and contextual factors into how people are susceptible to cognitive biases. The manifestation of cognitive biases are influenced by user characteristics and interaction contexts. Therefore, biases are not always pronounced in every individual and scenario. Measured through self-assessments (such as Cognitive Reflection Test and Wilson-Patterson Conservatism Scales), I investigate how do individual and contextual factors influence the occurrences of confirmation bias in three information interaction scenarios: seeking, interpreting, and seeking polarising information. [Accepted at CHI ‘25]
I map out the field’s discussion and research around the issue of cognitive biases. Through a systematic scoping review of HCI articles investigating cognitive biases (from 2010 to 2024), I document cognitive biases that present in the interaction with computers and chart how researchers study them from the HCI angle. The findings suggest computing systems can be designed to trigger biases in people and manipulate their judgement. Meanwhile, the very same technologies can be used for mitigating undesired effects of cognitive biases. Therefore, HCI researchers study these biases to derive designs of technologies that take into account biases in people and computing systems. [Accepted at CHI ‘25]
I sketch out a research agenda for designing technologies to support critical thinking in people and fortify them from misinformation and online manipulation. I document the discussions in three workshops and formulate HCI-side solutions that help limit the spread of misinformation through user interfaces and effective interventions that foster deliberate thinking in people and skills they need to conduct themselves online.
Prior to that, I obtained a Master of Information Science and Technology from Osaka University in Japan, where I received the Japanese Government Scholarship (MEXT). My master’s thesis titled Towards Multimodal Office Task Performance Estimation led me to develop research interests in cognition-aware computing and physiological sensing. Prior to Japan, I completed a Bachelor of Computer Engineering (1st class honours) from Chulalongkorn University, Thailand.
Academic Service and Volunteering
- CHI ‘24 LBW Associate Chair
- External Reviewer: CHI (25, 24, 23), ISS (24), CHI LBW (25, 24), MobileHCI LBW (24, 23) MUM (23), HAI (23), ISWC (2023), SMC (24)
- Program Chair, 2024 CIS Doctoral Colloquium
- Committee Member, CIS Graduate Researcher Society (2022-2024)
- Student Volunteer at CHI ‘25, CHI ‘23, and VIS ‘23
Awards
- Special Recognition for Outstanding Reviews (CHI’25 LBW, CHI ‘24, and ISS ‘24 Febuary Round)
- Melbourne Plus - People Leadership (2024)
- Melbourne Research Scholarship (2021)
- Japanese Government Scholarship (2018)
Selected Publications
- Nattapat Boonprakong, Benjamin Tag, Jorge Goncalves, and Tilman Dingler. 2025. How Do HCI Researchers Study Cognitive Biases? A Scoping Review. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26–May 01, 2025, Yokohama, Japan. ACM, New York, NY, USA, 20 pages. Paper
- Nattapat Boonprakong, Saumya Pareek, Benjamin Tag, Jorge Goncalves, and Tilman Dingler. 2025. Assessing Susceptibility Factors of Confirmation Bias in News Feed Reading. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26–May 01, 2025, Yokohama, Japan. ACM, New York, NY, USA, 19 pages. Paper
- Nattapat Boonprakong, Xiuge Chen, Catherine Davey, Benjamin Tag, and Tilman Dingler. 2023. Bias-Aware Systems: Exploring Indicators for the Occurrences of Cognitive Biases when Facing Different Opinions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ‘23). Association for Computing Machinery, New York, NY, USA, Article 27, 1–19. Honorable Mention Best Paper
- Nattapat Boonprakong, Benjamin Tag, and Tilman Dingler. 2023. Designing Technologies to Support Critical Thinking in an Age of Misinformation. In IEEE Pervasive Computing, vol. 22, no. 3, pp. 8-17, 1 July-Sept. 2023. Paper
- Nattapat Boonprakong, Tsukasa Kimura, Ken-ichi Fukui, Kazuya Okada, Masato Ito, Hiroshi Maruyama, Masayuki Numao. Towards Multimodal Office Task Performance Estimation. 2020. IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, ON, Canada, 2020, pp. 2695-2701. Paper
Invited Talks
- (RMIT TIGER Talk) Bias-Aware Systems: Understanding, Detecting, and Mitigating Cognitive Biases that Aid the Spread of Misinformation (November 9, 2023)
- (CIS PhD Confirmation Seminar) Understanding, Detecting, and Mitigating Cognitive Biases that Aid the Spread of Misinformation (October 21, 2022)
Teaching
- Head Tutor COMP90041 (Programming and Software Development): 2022-Present
- Tutor COMP90018 (Mobile Computing Systems Programming): 2024